Non-Classical monocytes display inflammatory features: Validation in Sepsis and Systemic Lupus Erythematous View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-11

AUTHORS

Ratnadeep Mukherjee, Pijus Kanti Barman, Pravat Kumar Thatoi, Rina Tripathy, Bidyut Kumar Das, Balachandran Ravindran

ABSTRACT

Given the importance of monocytes in pathogenesis of infectious and other inflammatory disorders, delineating functional and phenotypic characterization of monocyte subsets has emerged as a critical requirement. Although human monocytes have been subdivided into three different populations based on surface expression of CD14 and CD16, published reports suffer from contradictions with respect to subset phenotypes and function. This has been attributed to discrepancies in reliable gating strategies for flow cytometric characterization and purification protocols contributing to significant changes in receptor expression. By using a combination of multicolour flow cytometry and a high-dimensional automated clustering algorithm to confirm robustness of gating strategy and analysis of ex-vivo activation of whole blood with LPS we demonstrate the following: a. 'Classical' monocytes are phagocytic with no inflammatory attributes, b. 'Non-classical' subtype display 'inflammatory' characteristics on activation and display properties for antigen presentation and c. 'Intermediate' subtype that constitutes a very small percentage in circulation (under physiological conditions) appear to be transitional monocytes that display both phagocytic and inflammatory function. Analysis of blood from patients with Sepsis, a pathogen driven acute inflammatory disease and Systemic Lupus Erythmatosus (SLE), a chronic inflammatory disorder validated the broad conclusions drawn in the study. More... »

PAGES

13886

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/srep13886

    DOI

    http://dx.doi.org/10.1038/srep13886

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1051140591

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/26358827


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